Projects

ICSI hosts basic, pre-competitive research of fundamental importance to computer science and engineering. Projects are chosen based on the interests of the Institute’s principal investigators and the strengths of its researchers and affiliated UC Berkeley faculty.

Recent projects are listed below; the full list of each group's projects is accessible via the links listed in the sidebar.

Project OUCH has been completed, and the final report is available here.

The central idea behind this project is that if we want to improve recognition performance through acoustic modeling, then we should first quantify how the current best model — the hidden Markov model (HMM) — fails to adequately model speech data and how these failures impact recognition accuracy. We are undertaking a diagnostic analysis that is an essential component of statistical modeling but, for various reasons, has been largely ignored in the field of speech recognition. In particular, we believe that previous attempts to improve upon the HMM have largely failed because this diagnostic information was not readily available. In our initial research, we are using simulation and a novel sampling process to generate pseudo test data that deviate from the HMM in a controlled fashion. These processes allow us to generate pseudo data that, at one extreme, agree with all of the model's assumptions, and at the another extreme, deviate from the model in exactly the way real data does. In between, we precisely control the degree of data/model mismatch. By measuring recognition performance on this pseudo test data, we are able to quantify the effect of this controlled data/model residual on recognition accuracy.

Location estimation is the task of estimating the geo-coordinates of the content recorded in digital media The Berkeley Multimodal Location Estimation project aims to leverage the GPS-tagged media available on the web as training set for an automatic location estimator. The idea is that visual and acoustic cues can narrow down the possible recording location for a given image, video, or audio track. We also investigate the human baseline of location estimation, i.e. how well does a human do in comparison to a computer?

Researchers are exposing the ways in which it is possible to aggregate public and seemingly innocuous information from different media and Web sites to attack the privacy of users. The project seeks to help users, particularly younger ones, understand the privacy implications of the information they share publicly on the Internet and to help them understand what control they can exercise over it.

In collaboration with Case Western Reserve University, we are investigating foundation architectural constructs that bring users into networked systems in a way that has to this point not been possible. Rather than relegating users to an artifact of the application layer, we seek to accommodate users and their relationships at all layers of the system and to give users new controls over how their traffic is handled by the system.

Today's routers and switches are both complicated and closed. The forwarding path on these boxes involve sophisticated ASICs, and the large base of installed software is typically closed and proprietary. Thus, functionality can only evolve on hardware design timescales, and only through the actions of the vendors. At ICSI, in collaboration with our colleagues at Stanford University, we are pursuing a radically different approach which we call Open Software-Defined Networks.

Along with research groups around the world, we are exploring fundamental questions about Internet architecture. In particular, we are, "If we were to redesign the Internet, what would it look like?" This effort involves looking at all aspects of the Internet architecture, including addressing, intradomain routing, interdomain routing, naming, name resolution, network API, monitoring, and troubleshooting. Moreover, the effort involves both in-depth investigations of these isolated topics, and a synthesis of these aspects into a coherent and comprehensive future Internet architecture.

We conduct extensive research on technology for analyzing network traffic streams to detect attacks, either in "real time" as they occur, or in support of post facto forensic exploration. The particular context for much of this research is the open-source "Bro" network intrusion detection system authored by ICSI staff. Bro runs 24x7 operationally at a number of institutes, and we have particularly close ties with the Lawrence Berkeley National Laboratory, where Bro deployments have formed an integral part of the Institute's cybersecurity operations for more than a decade.

One of the most disturbing recent shifts in Internet attacks has been the change from attackers motivated by glory or vanity to attackers motivated by commercial (criminal) gain. This shift threatens to greatly accelerate the "arms race" between defenders developing effective counters to attacks and highly motivated, well funded attackers finding new ways to circumvent these innovations.

Typical Web pages may contain numerous third-party components, ranging from advertisement networks to analytics tools to third-party APIs necessary for page function. All of these components may leak information to third parties about the users' current activity. We are attempting to quantify this information leakage through a policy written in the Bro IDS. Preliminary analysis paints a bleak picture, as more than 1 percent of all HTTP requests observed by ICSI users are deliberately leaking information just through Google Analytics alone.

This project is concerned with the discovery of highly speaker-characteristic behaviors ("speaker performances") for use in speaker recognition and related speech technologies. The intention is to move beyond the usual low-level short-term spectral features which dominate speaker recognition systems today, instead focusing on higher-level sources of speaker information, including idiosyncratic word usage and pronunciation, prosodic patterns, and vocal gestures.

Massive numbers of video clips are generated daily on many types of consumer electronics and uploaded to the Internet. In contrast to videos that are produced for broadcast or from planned surveillance, the "unconstrained" video clips produced by anyone who has a digital camera present a significant challenge for manual as well as automated analysis. Such clips can include any possible scene and events, and generally have limited quality control.

In 1978 The World Color Survey (WCS) collected color naming data in 110 unwritten languages from around the world. The ICSI WCS staff (Paul Kay and Richard Cook of ICSI, Terry Regier of University of Chicago) put these data into a single database, available to the scientific community. Several outside laboratories have already used this database for studies.

The NTL (Neural Theory of Language) project of the AI Group works in collaboration with other units on the UC Berkeley campus and elsewhere. It combines basic research in several disciplines with applications to natural language understanding systems. Basic efforts include studies in the computational, linguistic, neurobiological, and cognitive bases for language and thought. This research continues to yield a variety of theoretical and practical findings.

The FrameNet project is building a semantically-rich lexicon of English and a corresponding set of annotated texts, based on more than 600 semantic frames and 130,000 sentences. Comparable FrameNet projects are underway for Spanish, German, and other languages. By providing a layered semantic representation of text, FrameNet delivers a key component of next-generation question answering, machine translation, and other natural language processing applications. Learn more on the FrameNet Web site.

A long-term goal of computational molecular biology is to extract, from large data sets, information about how proteins work together to carry out life processes at a cellular level. We are investigating protein-protein interaction (PPI) networks, in which the vertices are the proteins within a species and the edges indicate direct interactions between proteins. Our goal is to discover conserved protein modules: richly interacting sets of proteins whose patterns of interaction are conserved across two or more species.

In these studies, sets of cases (individuals carrying a disease) and controls (background population) are collected and genotyped for genetic variants, normally single nucleotide polymorphisms (SNPs). Our group is collaborating closely with groups of geneticists and epidimiologists who have collected such samples. We take part in the analysis of these studies, and in some cases also in the design of the studies.